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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Assessing the PACE of California residential solar deployment: Impacts of Property Assessed Clean Energy programs on residential solar photovoltaic deployment in California, 2010-2015

A new study by Berkeley Lab found that residential Property Assessed Clean Energy (R-PACE) programs increased deployment of residential solar photovoltaic (PV) systems in California, raising it by about 7-12% in cities that adopt these programs. R-PACE is a financing mechanism that uses a voluntary property tax assessment, paid off over time, to facilitate energy improvements and, in some jurisdictions, water and resilience measures. While previous studies demonstrated that early, regional R-PACE programs increased solar PV deployment, this new analysis is the first to demonstrate these impacts from the large, statewide R-PACE programs dominating the California market today, which use private capital to fund the upfront costs of the improvements. Berkeley Lab estimated the impacts using econometric techniques on two samples: -Large cities only, allowing annual demographic and economic data as control variables -All California cities, without these annual data Analysis of both samples controls for several factors other than R-PACE that would be expected to drive solar PV deployment. We infer that on average, cities with R-PACE programs were associated with greater solar PV deployment in our study period (2010-2015). In the large cities sample, solar PV deployment in jurisdictions with R-PACE programs was higher by 1.1 watts per owner-occupied household per month, or 12%. Across all cities, solar PV deployment in jurisdictions with R-PACE programs was higher by 0.6 watts per owner-occupied household per month, or 7%. The large cities results are statistically significant at conventional levels; the all-cities results are not. The estimates imply that the majority of solar PV deployment financed by R-PACE programs would likely not have occurred in their absence. Results suggest that R-PACE programs have increased PV deployment in California even in relatively recent years, as R-PACE programs have grown in market share and as alternate approaches for financing solar PV have developed. The U.S. Department of Energy’s Building Technologies Office supported this research.

14 SOLAR ENERGY↗
NASA NTRS2023

Long-term 4.6 µm Variability in Brown Dwarfs and a New Technique for Identifying Brown Dwarf Binary Candidates

Using a sample of 361 nearby brown dwarfs, we have searched for 4.6 μm variability, indicative of large-scale rotational modulations or large-scale, long-term changes on timescales of over 10 yr. Our findings show no statistically significant variability in Spitzer's Infrared Array Camera (IRAC) channel 2 (ch2) or Wide-field Infrared Survey Explorer W2 photometry. For Spitzer the ch2 1σ limits are ∼8 mmag for objects at 11.5 mag and ∼22 mmag for objects at 16 mag. This corresponds to no variability above 4.5% at 11.5 mag and 12.5% at 16 mag. We conclude that highly variable brown dwarfs, at least two previously published examples of which have been shown to have 4.6 μm variability above 80 mmag, are very rare. While analyzing the data, we also developed a new technique for identifying brown dwarf binary candidates in Spitzer data. We find that known binaries have IRAC ch2 point response function (PRF) flux measurements that are consistently dimmer than aperture flux measurements. We have identified 59 objects that exhibit such PRF versus aperture flux differences and are thus excellent binary brown dwarf candidates.

Hunter Brooks↗
NASA NTRS2001

Robust Airfoil Optimization to Achieve Consistent Drag Reduction Over a Mach Range

We prove mathematically that in order to avoid point-optimization at the sampled design points for multipoint airfoil optimization, the number of design points must be greater than the number of free-design variables. To overcome point-optimization at the sampled design points, a robust airfoil optimization method (called the profile optimization method) is developed and analyzed. This optimization method aims at a consistent drag reduction over a given Mach range and has three advantages: (a) it prevents severe degradation in the off-design performance by using a smart descent direction in each optimization iteration, (b) there is no random airfoil shape distortion for any iterate it generates, and (c) it allows a designer to make a trade-off between a truly optimized airfoil and the amount of computing time consumed. For illustration purposes, we use the profile optimization method to solve a lift-constrained drag minimization problem for 2-D airfoil in Euler flow with 20 free-design variables. A comparison with other airfoil optimization methods is also included.

Li, Wu↗
DOE OSTI2024

Fast and Flexible Inference Framework for Continuum Reverberation Mapping Using Simulation-based Inference with Deep Learning

Continuum reverberation mapping (CRM) of active galactic nuclei (AGN) monitors multiwavelength variability signatures to constrain accretion disk structure and supermassive black hole (SMBH) properties. The upcoming Vera Rubin Observatory’s Legacy Survey of Space and Time will survey tens of millions of AGN over the next decade, with thousands of AGN monitored with almost daily cadence in the deep drilling fields. However, existing CRM methodologies often require long computation time and are not designed to handle such large amounts of data. In this paper, we present a fast and flexible inference framework for CRM using simulation-based inference (SBI) with deep learning to estimate SMBH properties from AGN light curves. We use a long short-term memory summary network to reduce the high dimensionality of the light curve data and then use a neural density estimator to estimate the posterior of SMBH parameters. Using simulated light curves, we find SBI can produce more accurate SMBH parameter estimation with 10 3 –10 5 times speed up in inference efficiency compared to traditional methods. The SBI framework is particularly suitable for wide-field CRM surveys as the light curves will have identical observing patterns, which can be incorporated into the SBI simulation. We explore the performance of our SBI model on light curves with irregular-sampled, realistic observing cadence and alternative variability characteristics to demonstrate the flexibility and limitation of the SBI framework.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Characterizing the Gamma-Ray Variability of the Brightest Flat Spectrum Radio Quasars Observed with the Fermi LAT

Almost 10 yr of γ-ray observations with the Fermi Large Area Telescope have revealed extreme γ-ray outbursts from flat spectrum radio quasars (FSRQs), temporarily making these objects the brightest γ-ray emitters in the sky. Yet, the location and mechanisms of the γ-ray emission remain elusive. We characterize long-term γ-ray variability and the brightest γ-ray flares of six FSRQs. Consecutively zooming in on the brightest flares, which we identify in an objective way through Bayesian blocks and a hill-climbing algorithm, we find variability on subhour timescales and as short as minutes for two sources in our sample (3C 279 and CTA 102) and weak evidence for variability at timescales less than the Fermi satellite's orbit of 95 minutes for PKS 1510–089 and 3C 454.3. This indicates extremely compact emission regions in the jet. We do not find any signs of γ-ray absorption in the broad-line region (BLR), which indicates that γ-rays are produced at distances greater than hundreds of gravitational radii from the central black hole. This is further supported by a cross-correlation analysis between γ-ray and radio/millimeter light curves, which is consistent with γ-ray production at the same location as the millimeter core for 3C 273, CTA 102, and 3C 454.3. The inferred locations of the γ-ray production zones are still consistent with the observed decay times of the brightest flares if the decay is caused by external Compton scattering with BLR photons. Yet, the minute-scale variability is challenging to explain in such scenarios.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Use of Aerosol Observations From Aircraft in Satellite Remote Sensing and Modelling Comparisons

Aerosol extensive and intensive properties vary throughout the world and remain one of the largest uncertainties in determining future climate both because of difficulties in their measurement and their modelled behaviors. Here we highlight the contributions of airborne sampling by the sunphotometer 4STAR (Spectrometers for Sky-Scanning Sun Tracking Atmospheric Research) from two different parts of the world; Korean peninsula and region during the KORUS-AQ experiment (KORean-US Air Quality in May-June 2016) and over the South East Atlantic during ORACLES (ObseRvations of CLouds above Aerosols and their intEractionS in August-September-October 2016, 2017, and 2018) field campaign. The high temporal and spatial resolution, afforded by airborne sampling during KORUS-AQ, are used to determine the variability of aerosol intensive and extensive properties, which is a metric than can be compared in between multiple different observations and models, even over varying surfaces and spanning multiple different aerosol emission sources. We show the consistency over spatial scales of the AOD (Aerosol Optical Depth), and the aerosol intensive properties (Angstrom exponent - AE, fine mode fraction - FMF) observed by 4STAR, GOCI (Geostationary Ocean Color Imager Yonsei aerosol retrieval v2), MERRA-2 reanalysis (Modern-Era Retrospective Analysis for Research and Applications, v2), and from airborne in situ aerosol optical measurements by LARGE (NASA Langley Aerosol Research Group Experiment). The majority of AODs due to fine mode aerosol is observed at altitudes lower than 2 km and is dependent on the prevailing meteorological conditions. AE and FMF are found to be more spatially variable than AOD during all of KORUS-AQ, even when accounting for potential sampling biases. This may indicate that microphysical processes like aerosol particle formation, growth, and coagulation impact the dominant aerosol size at shorter scales than their combined effect on the aerosol optical depth by the aerosol emission, transport, and removal. Averaging between measurements and model, the distance at which the correlation to itself is reduced by 15% is 65 km for AOD, and 22.7 km for AE. Vertically resolved measurement from an aircraft enable the direct measurements of aerosols overlying clouds. When aerosol overlie bright clouds, their radiative impact on the incident light can be either positive or negative. This difference in radiative impact promotes difficulties in remote sensing aerosol properties, which have shown biases in AOD retrievals when clouds are underneath. The AOD above clouds measured by 4STAR during ORACLES are used to build and improve upon the current Near-Real-Time MODACAERO algorithm for above cloud AOD from MODIS, into a continuity product for NASA EOS/SNPP/JPSS.

Aerosol↗
DOE OSTI2021

Band structure dependent electronic localization in macroscopic films of single-chirality single-wall carbon nanotubes

Significant understanding has been achieved over the last few decades regarding chirality-dependent properties of single-wall carbon nanotubes (SWCNTs), primarily through single-tube studies. However, macroscopic manifestations of chirality dependence have been limited, especially in electronic transport, despite the fact that such distinct behaviors are needed for many applications of SWCNT-based devices. In addition, developing reliable transport theory is challenging since a description of localization phenomena in an assembly of nanoobjects requires precise knowledge of disorder on multiple spatial scales, particularly if the ensemble is heterogeneous. Here, we report an observation of pronounced chirality-dependent electronic localization in temperature and magnetic field dependent conductivity measurements on macroscopic films of single-chirality SWCNTs. The samples included large-gap semiconducting (6,5) and (10,3) films, narrow-gap semiconducting (7,4) and (8,5) films, and armchair metallic (6,6) films. Experimental data and theoretical calculations revealed Mott variable-range-hopping dominated transport in all samples, while localization lengths fall into three distinct categories depending on their band gaps. Armchair films have the largest localization length. Here our detailed analyses on electronic transport properties of single-chirality SWCNT films provide significant new insight into electronic transport in ensembles of nanoobjects, offering foundations for designing and deploying macroscopic SWCNT solid-state devices.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Comparing generalized ensemble methods for sampling of systems with many degrees of freedom

Here, we compare two standard replica exchange methods using temperature and dielectric constant as the scaling variables for independent replicas against two new corresponding enhanced sampling methods based on non-equilibrium statistical cooling (temperature) or descreening (dielectric). We test the four methods on a rough 1D potential as well as for alanine dipeptide in water, for which their relatively small phase space allows for the ability to define quantitative convergence metrics. We show that both dielectric methods are inferior to the temperature enhanced sampling methods, and in turn show that temperature cool walking (TCW) systematically outperforms the standard temperature replica exchange (TREx) method. We extend our comparisons of the TCW and TREx methods to the 5 residue met-enkephalin peptide, in which we evaluate the Kullback-Leibler divergence metric to show that the rate of convergence between two independent trajectories is faster for TCW compared to TREx. Finally we apply the temperature methods to the 42 residue amyloid-β peptide in which we find non-negligible differences in the disordered ensemble using TCW compared to the standard TREx. All four methods have been made available as software through the OpenMM Omnia software consortium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2026

High Temperature Dielectric Properties and Differential Scanning Calorimetry of Lunar Simulants

To guide development of microwave process technology that could be used during in situ construction on the Moon, we measured the high-temperature basic dielectric properties (εʹ and εʺ) of 17 lunar simulants and related materials. In order to confidently use these data one needs to understand the data’s strengths and weaknesses. Therefore, a goal of this publication is to provide insights into the comparative effects of sample composition, pre-treatments, experimental variables, high temperatures, and other factors on the measured response. The dielectric measurements were performed using the cavity perturbation method over a temperature range between room temperature to 1000 °C, or higher, and provided the real and imaginary components of permittivity at six frequencies. The utility of the original values was limited by the varying density of the pellets used in the measurement. Therefore, all of the εʹ and εʺ measurements at the frequency of 2466 MHz have been scaled to a constant density, 1.75 g/cm 3 . Here the data are presented as graphs chosen to aid analysis within and across simulant groups. To gain additional insight into the processes happening at the elevated temperatures in the dielectric measurements, heat capacity data was obtained using differential scanning calorimetry (DSC) on several of the simulant materials. Our data show that over the frequency range 397 MHz – 2985 MHz a material’s behavior does not greatly change, as compared to the scale of differences observed between lunar mare and highland simulants at high temperatures. For example at 1000 °C, the mare simulant JSC-1A absorbs 10 times more power than the highland simulant NUW-LHT-5M. We observe that as melting temperatures are reached both permittivity and dielectric loss rise non-linearly, helping to explain thermal runaway during microware heating. Our data show that even less than a few weight % of many non-lunar minerals, and the use of mixtures in simulants can affect the dielectric behavior at higher temperatures. A comparison of our results with published dielectric data for Apollo samples and with remote sensing of the Moon supports the conclusion the simulants and lunar material at room temperature have very similar dielectric values.

Differential Scanning Calorimetry↗
NASA NTRS2007

Multispecies Biofilm Development on Space Station Heat Exhanger Core Material

Investigations of microbial contamination of the cooling system aboard the International Space Station (ISS) suggested that there may be a relationship between heat exchanger (HX) materials and the degree of microbial colonization and biofilm formation. Experiments were undertaken to test the hypothesis that biofilm formation is influenced by the type and previous exposure of HX surfaces. Acidovorax delafieldii, Comamonas acidovorans, Hydrogenophaga pseudoflava, Pseudomonas stutzeri, Sphingomonas paucimobilis, and Stenotrophomonas maltophilia, originally isolated from ISS cooling system fluid, were cultured on R2A agar and suspended separately in fresh filter-sterilized ISS cooling fluid, pH 8.3. Initial numbers in each suspension ranged from 10(exp 6)-10(exp 7) CFU/ml, and a mixture contained greater than 10(exp 7) CFU/ml. Coupons of ISS HX material, previously used on orbit (HXOO) or unused (HXUU), polycarbonate (PC) and 316L polished stainless steel (SS) were autoclaved, covered with multispecies suspension in sterile tubes and incubated in the dark at ambient (22-25 C). Original HX material contained greater than 90% Ni, 4.5% Si, and 3.2% B, with a borate buffer. For approximately 10 weeks, samples of fluid were plated on R2A agar, and surface colonization assessed by SYBR green or BacLight staining and microscopy. Suspension counts for the PC and SC samples remained steady at around 10(exp 7) CFU/ml. HXUU counts declined about 1 log in 21 d then remained steady, and HXOO counts declined 2 logs in 28 d, fluctuated and stabilized about 10(exp 3) CFU/ml from 47-54 d. Predominantly yellow S. paucimobilis predominated on plates from HXOO samples up to 26 d, then white or translucent colonies of other species appeared. All colony types were seen on plates from other samples throughout the trial. Epifluorescence microscopy indicated microbial growth on all surfaces by 21 d, followed by variable colonization. After 54 d, all but the HXOO samples had well-distributed live and dead cells; the HXOO samples had few cells and most were live by BacLight. The results suggest that HX materials themselves are inhibiting microbial growth on the surfaces. The HX exposed on orbit to cooling system fluid inhibited growth of some species originally isolated from the system, whereas the unused HX material had a moderate effect compared to no inhibition with PC or SS controls. It is possible that chemistry or microbiology of the ISS system increased deposition of inhibitory compounds on the HXOO coupon surfaces; these may inhibit inoculated species to differing degrees.

Pyle, B. H.↗
DOE OSTI2022

Clean quartz matters for cosmogenic nuclide analyses: An exploration of the importance of sample purity using the CRONUS-N reference material

We report reference materials are key for assessing inter-laboratory variability and measurement quality, and for placing analytical uncertainty bounds on sample analyses. Here, we investigate four years of data resulting from repeated processing of the CRONUS-N reference material for cosmogenic 10 Be and 26 Al analyses. At University of Vermont, we prepared a CRONUS-N aliquot with most of our sample batches from 2013 to 2017; these reference material samples were then distributed to four different accelerator mass spectrometry facilities, yielding 73 10 Be analyses and 58 26 Al analyses. We determine CRONUS-N 10 Be concentrations of (2.26 ± 0.14) x 10 5 atoms g -1 (n = 73, mean, 1 SD) and 26 Al concentrations of (1.00 ± 0.08) x 10 6 atoms g -1 (n = 58, mean, 1 SD). We find a reproducibility of 6.3% for 10 Be and 7.7% for 26 Al (relative standard deviations). We also document highly variable 27 Al and Mg concentrations and a 10 Be dispersion twice as large as the mean AMS analytic uncertainty. Analyses of the CRONUS-N material with and without density separation demonstrate that non-quartz minerals are present in the material and have a large impact on measured concentrations of 27 Al, 10 Be, and impurities; these non-quartz minerals represent only a very small portion of the total mass (0.6–0.8%) but have a disproportionally large effect on the resulting data. Our results highlight the importance of completely removing all non-quartz mineral phases from samples prior to Be/Al extraction for the determination of in situ cosmogenic 10 Be and 26 Al concentrations.

58 GEOSCIENCES↗
DOE OSTI2024

Geophysical methods reveal the soil architecture and subsurface stratigraphic heterogeneities across land-lake interfaces along Lake Erie

Abstract Purpose The land-lake interface is a unique zone where terrestrial and aquatic ecosystems meet, forming part of the Earth’s most geochemically and biologically active zones. The unique characteristics of this interface are yet to be properly understood due to the inherently high spatiotemporal variability of subsurface properties, which are difficult to capture with the traditional soil sampling methods. Geophysical methods offer non-invasive techniques to capture variabilities in soil properties at a high resolution across various spatiotemporal scales. Methods We combined electromagnetic induction (EMI), electrical resistivity tomography (ERT), and ground penetrating radar (GPR) with data from soil cores and in situ sensors to investigate hydrostratigraphic heterogeneities across land-lake interfaces along the western basin of Lake Erie. Results EMI revealed high spatial heterogeneities in ECa distribution across the land-lake interfaces, with higher values in the wetland and transition zones compared to the upland zone. Soil ECa maps matched soil maps from a public database with the hydric soil units delineated as high conductivity zones (ECa > 40 mS/m). ERT and GPR showed vertical variation in soil properties with clear stratigraphic boundaries, and correlation of ERT profiles with lithologs from piezometers revealed the stratigraphic units of silt–clay and till sequence down to 3.5 m depth which are consistent with the surficial geology of the study area. Conclusions These results validate the use of multiple geophysical methods for extrapolating soil properties and mapping stratigraphic structures at land-lake interfaces, thereby providing the missing information required to improve the earth system model (ESM) of coastal interfaces.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Computation of Variability in the Average Thermal and Mechanical Properties of a Melt-infiltrated Sic/sic Composite

Thermal conductivity and tensile properties (elastic modulus, proportional limit strength, inplane tensile strength, and strain to failure) of a SiC/SiC composite were experimentally determined at 816 and 1204 C. Tests were performed at room temperature on the same material to obtain interlaminar shear and tensile strength. For each thermal and mechanical property 24 tests were conducted to capture the variation. A random sampling method was used to quantify the variability exhibited by the mean values of the thermal and mechanical properties. The minimum number of tests required to characterize the mean value of each thermal or mechanical property for the composite was determined by varying the group size of the random sample.

Kalluri, Sreeramesh↗
NASA NTRS2007

Sampling Biases in MODIS and SeaWiFS Ocean Chlorophyll Data

Although modem ocean color sensors, such as MODIS and SeaWiFS are often considered global missions, in reality it takes many days, even months, to sample the ocean surface enough to provide complete global coverage. The irregular temporal sampling of ocean color sensors can produce biases in monthly and annual mean chlorophyll estimates. We quantified the biases due to sampling using data assimilation to create a "truth field", which we then sub-sampled using the observational patterns of MODIS and SeaWiFS. Monthly and annual mean chlorophyll estimates from these sub-sampled, incomplete daily fields were constructed and compared to monthly and annual means from the complete daily fields of the assimilation model, at a spatial resolution of 1.25deg longitude by 0.67deg latitude. The results showed that global annual mean biases were positive, reaching nearly 8% (MODIS) and >5% (SeaWiFS). For perspective the maximum interannual variability in the SeaWiFS chlorophyll record was about 3%. Annual mean sampling biases were low (<3%) in the midlatitudes (between -40deg and 40deg). Low interannual variability in the global annual mean sampling biases suggested that global scale trend analyses were valid. High latitude biases were much higher than the global annual means, up to 20% as a basin annual mean, and over 80% in some months. This was the result of the high solar zenith angle exclusion in the processing algorithms. Only data where the solar angle is <75deg are permitted, in contrast to the assimilation which samples regularly over the entire area and month. High solar zenith angles do not facilitate phytoplankton photosynthesis and consequently low chlorophyll concentrations occurring here are missed by the data sets. Ocean color sensors selectively sample in locations and times of favorable phytoplankton growth, producing overestimates of chlorophyll. The biases derived from lack of sampling in the high latitudes varied monthly, leading to artifacts in the apparent seasonal cycle from ocean color sensors. A false secondary peak in chlorophyll occurred in May-August, which resulted from lack of sampling in the Antarctic.

Gregg, Watson W.↗
DOE OSTI2019

Multivariate Pointwise Information-Driven Data Sampling and Visualization

With increasing computing capabilities of modern supercomputers, the size of the data generated from the scientific simulations is growing rapidly. As a result, application scientists need effective data summarization techniques that can reduce large-scale multivariate spatiotemporal data sets while preserving the important data properties so that the reduced data can answer domain-specific queries involving multiple variables with sufficient accuracy. While analyzing complex scientific events, domain experts often analyze and visualize two or more variables together to obtain a better understanding of the characteristics of the data features. Therefore, data summarization techniques are required to analyze multi-variable relationships in detail and then perform data reduction such that the important features involving multiple variables are preserved in the reduced data. To achieve this, in this work, we propose a data sub-sampling algorithm for performing statistical data summarization that leverages pointwise information theoretic measures to quantify the statistical association of data points considering multiple variables and generates a sub-sampled data that preserves the statistical association among multi-variables. Using such reduced sampled data, we show that multivariate feature query and analysis can be done effectively. The efficacy of the proposed multivariate association driven sampling algorithm is presented by applying it on several scientific data sets.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

Variability in the vacuum-ultraviolet transmittance of magnesium fluoride windows

Sample window materials tested during the development of a domed magnesium fluoride detector window for the Hubble Space Telescope's Imaging Spectrograph are noted to exhibit wide variability in VUV transmittance; a test program was accordingly instituted to maximize a prototype domed window's transmittance. It is found that VUV transmittance can be maximized if the boule from which the window is fashioned is sufficiently large to allow such a component to be cut from the purest available portion of the boule.

Herzig, Howard↗
DOE OSTI2019

The effect of core composition on iron isotope fractionation between planetary cores and mantles

We have conducted high-pressure, high-temperature isotope exchange experiments between molten silicate and molten Fe–Si–C-alloys to constrain the effect of Si on equilibrium Fe isotope fractionation during planetary core formation. The values of Δ 57 Fe Metal-Silicate at 1850 °C and 1 GPa determined by high-resolution MC-ICP-MS in this study range from -0.013 ± 0.054‰ (2SE) to 0.072 ± 0.085‰ with 1.34–8.14 atom % Si in the alloy, respectively. These results, although not definitive on their own, are consistent with previous experimental results from our group and a model in which elements that substitute for Fe atoms in the alloy structure (i.e., Ni, S, and Si) induce a fractionation of Fe isotopes between molten silicate and molten Fe-alloys during planetary differentiation. Using in situ synchrotron X-ray diffraction data for molten Fe-rich alloys from the literature, we propose a model to explain this fractionation behavior in which impurity elements in Fe-alloys cause the nearest neighbor atomic distances to shorten, thereby stiffening metallic bonds and increasing the preference of the alloy for heavy Fe isotopes relative to the silicate melt. This fractionation results in the bulk silicate mantles of the smaller terrestrial planets and asteroids becoming isotopically light relative to chondrites, with an enrichment of heavy Fe isotopes in their cores, consistent with magmatic iron meteorite compositions. Our model predicts a bulk silicate mantle $δ^{57}$Fe ranging from -0.01‰ to -0.12‰ for the Moon, -0.06‰ to -0.33‰ for Mars, and -0.08‰ to -0.33‰ for Vesta. Independent estimates of the $δ^{57}$Fe of primitive mantle source regions that account for Fe isotope fractionation during partial melting agree well with these ranges for all three planetary bodies and suggest that Mars and Vesta have cores with impurity (i.e., Ni, S, Si) abundances near the low end of published ranges. Therefore, we favor a model in which core formation results in isotopically light bulk silicate mantles for the Moon, Mars, and Vesta. The processes of magma ocean crystallization, mantle partial melting, and fractional crystallization of mantle-derived melts are all likely to result in heavy Fe isotope enrichment in the melt phase, which can explain why basaltic samples from these planetary bodies have variable Fe values consistently heavier than our bulk mantle estimates. Additionally, we find no clear evidence that Fe isotopes were fractionated to a detectable level by volatile depletion processes during or after planetary accretion, although it cannot be ruled out.

58 GEOSCIENCES↗
DOE OSTI2020

Fouling modeling and prediction approach for heat exchangers using deep learning

In this article, we develop a generalized and scalable statistical model for accurate prediction of fouling resistance using commonly measured parameters of industrial heat exchangers. This prediction model is based on deep learning where a scalable algorithmic architecture learns non-linear functional relationships between a set of target and predictor variables from large number of training samples. Here, the efficacy of this modeling approach is demonstrated for predicting fouling in an analytically modeled cross-flow heat exchanger, designed for waste heat recovery from flue-gas using room temperature water. The performance results of the trained models demonstrate that the mean absolute prediction errors are under 10 –4 KW –1 for flue-gas side, water side and overall fouling resistances. The coefficients of determination (R 2 ), which characterize the goodness of fit between the predictions and observed data, are over 99%. Even under varying levels of measurement noise in the inputs, we demonstrate that predictions over an ensemble of multiple neural networks achieves better accuracy and robustness to noise. We find that the proposed deep-learning fouling prediction framework learns to follow heat exchanger flow and heat transfer physics, which we confirm using locally interpretable model agnostic explanations around randomly selected operating points. Overall, we provide a robust algorithmic framework for fouling prediction that can be generalized and scaled to various types of industrial heat exchangers.

42 ENGINEERING↗